Logistic Regression for Insured Mortality Experience Studies

DOI10.1080/10920277.2015.1039135zbMath1414.62426OpenAlexW2182376331MaRDI QIDQ5379155

George Hrischenko, Zhiwei Zhu, David Wylde, Zhi Li, Michael Failor

Publication date: 28 May 2019

Published in: North American Actuarial Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10920277.2015.1039135

zbMATH Keywords

logistic regression modelinsured mortality experience

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Generalized linear models (logistic models) (62J12)

Related Items (2)

MULTI-STATE MODELLING OF CUSTOMER CHURN ⋮ A credibility approach of the Makeham mortality law

Uses Software

• rms
• aplore3

Cites Work

• Unnamed Item
• Modeling and Forecasting U.S. Mortality
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• The impact of the determinants of mortality on life insurance and annuities
• Modeling Surrender and Lapse Rates With Economic Variables
• Smoothing and forecasting mortality rates
• Applied Logistic Regression
• Multivariate Analysis of Pension Plan Mortality Data
• Regression modeling strategies. With applications to linear models, logistic regression and survival analysis

This page was built for publication: Logistic Regression for Insured Mortality Experience Studies